Optimizing Emergency Service Patient Scheduling Using Cloud Computing
DOI:
https://doi.org/10.5935/jetia.v12i61.3762Resumo
Emergency departments often struggle with issues like long wait times for patients, overcrowding, and poor use of resources. This study suggests a new system for scheduling patients in the cloud. The system aims to reduce waiting times and make the best use of resources. The system uses a way of deciding how to give resources to patients, where the priority is based on how bad their condition is, how old they are, if they are pregnant, and if they have other health problems. Patients are grouped together to keep things running smoothly. This way, new patients don't cause too much trouble. The proposed system was modelled and simulated using CloudSim. Simulation results show that the First-Come-First-Served method is less effective than a new method that assigns doctors to patients based on their arrival order. The new method raised the success rate by approximately 30 % when the patient-doctor ratio was not in balance. When there were a lot of people using the system, making more virtual machines helped make it work better. Cloud computing can help Emergency departments make better decisions quickly, work more efficiently, and improve patient care. In the future, we will work on making the scheduling process more accurate, making the system more adaptable, and using machine learning to predict future outcomes.
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Este trabalho está licenciado sob uma licença Creative Commons Attribution 4.0 International License.








